Literature DB >> 21287615

Role of conformational sampling in computing mutation-induced changes in protein structure and stability.

Elizabeth H Kellogg1, Andrew Leaver-Fay, David Baker.   

Abstract

The prediction of changes in protein stability and structure resulting from single amino acid substitutions is both a fundamental test of macromolecular modeling methodology and an important current problem as high throughput sequencing reveals sequence polymorphisms at an increasing rate. In principle, given the structure of a wild-type protein and a point mutation whose effects are to be predicted, an accurate method should recapitulate both the structural changes and the change in the folding-free energy. Here, we explore the performance of protocols which sample an increasing diversity of conformations. We find that surprisingly similar performances in predicting changes in stability are achieved using protocols that involve very different amounts of conformational sampling, provided that the resolution of the force field is matched to the resolution of the sampling method. Methods involving backbone sampling can in some cases closely recapitulate the structural changes accompanying mutations but not surprisingly tend to do more harm than good in cases where structural changes are negligible. Analysis of the outliers in the stability change calculations suggests areas needing particular improvement; these include the balance between desolvation and the formation of favorable buried polar interactions, and unfolded state modeling.
Copyright © 2010 Wiley-Liss, Inc.

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Year:  2010        PMID: 21287615      PMCID: PMC3760476          DOI: 10.1002/prot.22921

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  24 in total

1.  Contributions of the large hydrophobic amino acids to the stability of staphylococcal nuclease.

Authors:  D Shortle; W E Stites; A K Meeker
Journal:  Biochemistry       Date:  1990-09-04       Impact factor: 3.162

2.  Eris: an automated estimator of protein stability.

Authors:  Shuangye Yin; Feng Ding; Nikolay V Dokholyan
Journal:  Nat Methods       Date:  2007-06       Impact factor: 28.547

3.  The backrub motion: how protein backbone shrugs when a sidechain dances.

Authors:  Ian W Davis; W Bryan Arendall; David C Richardson; Jane S Richardson
Journal:  Structure       Date:  2006-02       Impact factor: 5.006

4.  Assessing computational methods for predicting protein stability upon mutation: good on average but not in the details.

Authors:  Vladimir Potapov; Mati Cohen; Gideon Schreiber
Journal:  Protein Eng Des Sel       Date:  2009-06-26       Impact factor: 1.650

Review 5.  Macromolecular modeling with rosetta.

Authors:  Rhiju Das; David Baker
Journal:  Annu Rev Biochem       Date:  2008       Impact factor: 23.643

6.  Predicting protein stability changes upon mutation using database-derived potentials: solvent accessibility determines the importance of local versus non-local interactions along the sequence.

Authors:  D Gilis; M Rooman
Journal:  J Mol Biol       Date:  1997-09-19       Impact factor: 5.469

7.  A potential smoothing algorithm accurately predicts transmembrane helix packing.

Authors:  R V Pappu; G R Marshall; J W Ponder
Journal:  Nat Struct Biol       Date:  1999-01

8.  Energetic contribution of side chain hydrogen bonding to the stability of staphylococcal nuclease.

Authors:  M P Byrne; R L Manuel; L G Lowe; W E Stites
Journal:  Biochemistry       Date:  1995-10-24       Impact factor: 3.162

9.  High-resolution structure prediction and the crystallographic phase problem.

Authors:  Bin Qian; Srivatsan Raman; Rhiju Das; Philip Bradley; Airlie J McCoy; Randy J Read; David Baker
Journal:  Nature       Date:  2007-10-14       Impact factor: 49.962

10.  ProTherm and ProNIT: thermodynamic databases for proteins and protein-nucleic acid interactions.

Authors:  M D Shaji Kumar; K Abdulla Bava; M Michael Gromiha; Ponraj Prabakaran; Koji Kitajima; Hatsuho Uedaira; Akinori Sarai
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

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  217 in total

1.  Amino acid coevolution induces an evolutionary Stokes shift.

Authors:  David D Pollock; Grant Thiltgen; Richard A Goldstein
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-30       Impact factor: 11.205

2.  High-throughput identification of protein mutant stability computed from a double mutant fitness landscape.

Authors:  Nicholas C Wu; C Anders Olson; Ren Sun
Journal:  Protein Sci       Date:  2015-12-08       Impact factor: 6.725

3.  Crucial roles of single residues in binding affinity, specificity, and promiscuity in the cellulosomal cohesin-dockerin interface.

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Journal:  J Biol Chem       Date:  2015-04-01       Impact factor: 5.157

4.  Mutational effects on stability are largely conserved during protein evolution.

Authors:  Orr Ashenberg; L Ian Gong; Jesse D Bloom
Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-09       Impact factor: 11.205

5.  Allosteric coupling in the bacterial adhesive protein FimH.

Authors:  Victoria B Rodriguez; Brian A Kidd; Gianluca Interlandi; Veronika Tchesnokova; Evgeni V Sokurenko; Wendy E Thomas
Journal:  J Biol Chem       Date:  2013-07-02       Impact factor: 5.157

6.  Computational design of a specific heavy chain/κ light chain interface for expressing fully IgG bispecific antibodies.

Authors:  K J Froning; A Leaver-Fay; X Wu; S Phan; L Gao; F Huang; A Pustilnik; M Bacica; K Houlihan; Q Chai; J R Fitchett; J Hendle; B Kuhlman; S J Demarest
Journal:  Protein Sci       Date:  2017-07-31       Impact factor: 6.725

7.  Recognition of a Key Anchor Residue by a Conserved Hydrophobic Pocket Ensures Subunit Interface Integrity in DNA Clamps.

Authors:  Senthil K Perumal; Xiaojun Xu; Chunli Yan; Ivaylo Ivanov; Stephen J Benkovic
Journal:  J Mol Biol       Date:  2019-04-30       Impact factor: 5.469

8.  Directed evolution of glycosyltransferase for enhanced efficiency of avermectin glucosylation.

Authors:  Ha-Young Choi; Hyun Seung Lim; Kwang-Hyun Park; Junheon Kim; Won-Gon Kim
Journal:  Appl Microbiol Biotechnol       Date:  2021-05-27       Impact factor: 4.813

9.  Molecular Dynamics and Umbrella Sampling Simulations Elucidate Differences in Troponin C Isoform and Mutant Hydrophobic Patch Exposure.

Authors:  Jacob D Bowman; Steffen Lindert
Journal:  J Phys Chem B       Date:  2018-08-02       Impact factor: 2.991

10.  Scientific benchmarks for guiding macromolecular energy function improvement.

Authors:  Andrew Leaver-Fay; Matthew J O'Meara; Mike Tyka; Ron Jacak; Yifan Song; Elizabeth H Kellogg; James Thompson; Ian W Davis; Roland A Pache; Sergey Lyskov; Jeffrey J Gray; Tanja Kortemme; Jane S Richardson; James J Havranek; Jack Snoeyink; David Baker; Brian Kuhlman
Journal:  Methods Enzymol       Date:  2013       Impact factor: 1.600

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